In 802.11 WLANs, the basic mechanism controlling medium access is the Distributed Coordination Function (DCF). This is a random access scheme, based on Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA).
In the DCF Basic Access mode, a station with a new packet to transmit selects a random backoff counter in the range [0,CW-1] where CW is the Contention Window. Time is slotted and, if the channel is sensed idle, the station first waits for a Distributed Inter-Frame Space (DIFS), then decrements the backoff counter for each physical layer (PHY) time slot. If the channel is detected busy, the countdown is halted and only resumed after the channel is detected idle again for a DIFS. Channel idle/busy status is sensed via:                CCA (Clear Channel Assessment) at physical level which is based on a carrier sense threshold for energy detection, e.g. −80 dBm. CCA is expected to be updated every physical slot time. It aims to detect transmissions within the interference range.        NAV (Network Allocation Vector) timer, also called virtual carrier sense, at media access control (MAC) level which is encapsulated in the MAC header of each 802.11 frame and is used to accurately predict the end of a received frame on air. It is naturally updated once per packet and can only gather information from stations within the decoding range.        
The channel is detected as idle if the CCA detects the channel as idle and the NAV is zero. Otherwise, the channel is detected as busy. A station transmits when the backoff counter reaches zero. The countdown process is illustrated schematically in FIG. 1. The 802.11 handshake imposes a half-duplex process whereby an acknowledgment (ACK) is always sent by the receiver upon the successful receipt of a unicast frame. The ACK is sent after a period of time called the Short Inter Frame Space (SIFS). As the SIFS is shorter than a DIFS, no other station is able to detect the channel idle for a DIFS until the end of the ACK transmission. If the transmitting station does not receive the ACK within a specified ACK Timeout, or it detects the transmission of a different packet on the channel, it reschedules the packet transmission according to the given backoff rules. CW is doubled with successive referrals until a maximum value (labeled as CWmax) and is reset to the minimum value (labeled as CWmin) after an ACKed transmission or once the maximum number of retransmission attempts is reached.
In addition to the foregoing Basic Access mode, an optional four way handshaking technique, known as Request-To-Send/Clear-To-Send (RTS/CTS) mode is available. Before transmitting a packet, a station operating in RTS/CTS mode reserves the channel by sending a special Request-To-Send short frame. The destination station acknowledges the receipt of an RTS by sending back a Clear-To-Send frame, after which normal packet transmission and ACK response occurs.
The DCF allows the fragmentation of packets into smaller units. Each fragment is sent as an ordinary 802.11 frame, which the sender expects to be ACKed. However, the fragments may be sent as a burst. That is, the first fragment contends for medium access as usual. When the first fragment is successfully sent, subsequent fragments are sent after a SIFS, so no collisions are possible. In addition, the medium is reserved using virtual carrier sense for the next fragment both at the sender (by setting the 802.11 NAV field in the fragment) and at the receiver (by updating the NAV in the ACK). This is illustrated schematically in FIG. 2. Burst transmission is halted after the last fragment has been sent or when loss is detected.
In a WLAN, link impairments (and so quality) are intimately linked to MAC operation and so typically cannot be estimated purely on the basis of PHY measurements such as signal-to-noise ratio (SNR). Nonetheless, higher level measurements such as throughput and delay statistics can have difficulty distinguishing between sources of channel impairment.
Tasks such as rate adaptation, channel allocation, contention window selection, power control and carrier sense selection—essential for improving and optimizing the network performance—all depend crucially on the availability of suitable link quality measurements, and it is the current lack of such measurements that underlies the poor performance of many approaches currently implemented in commodity hardware.
For example, at present, rate adaptation is in practice commonly based on the number of transmission retries (e.g. a typical approach might involve lowering the rate after n retries and increasing the rate after m successful transmissions). However, since the number of retries is affected not just by channel noise but is also closely linked to the number of contending stations (with associated collision related losses), this can easily lead to poor performance, see K Ramachandran et al., “Scalability analysis of Rate Adaptation Techniques in Congested IEEE 802.11 Networks: An ORBIT Testbed Comparative Study”, Proc. IEEE WoWMoM, 2007, the disclosure of which is incorporated herein by reference. Similar problems occur in the presence of hidden nodes, e.g. see S Wong, et al., “Robust Rate Adaptation for 802.11 Wireless Networks”, Proc. ACM MobiCom, 2006, the disclosure of which is incorporated herein by reference.
The consideration of link quality measurements is particularly topical since the trend towards increasingly dense wireless deployments is creating a real need for effective approaches for channel allocation/hopping, power control, etc. for interference mitigation see R. Gummadi, D. Wetherall, B. Greenstein, S. Seshan, “Understanding and Mitigating the Impact of RF Interference on 802.11 Networks”, Sigcomm 2007; and I. Broustis, J. Eriksson, S. Krishnamurthy, M. Faloutsos “Implications of Power Control in Wireless Networks: A Quantitative Study”, Proc. PAM, 2007, the disclosures of which are incorporated herein by reference.
Also, new applications such as mesh networks and media distribution within the home are creating new quality of service demands that require more sophisticated approaches to radio resource allocation, see Bruno, R.; Conti, M.; Gregori, “Mesh networks: commodity multi-hop ad hoc networks”, Proc. IEEE Communications Magazine, March 2005, the disclosure of which is incorporated herein by reference.
Previous work on 802.11 channel quality estimation can be classified into three categories. First, PHY link-level approaches use Signal-to-Noise Ratio (SNR)/Received Signal Strength Indication (RSSI) to directly estimate the link quality.
Second, MAC approaches rely on throughput and delay statistics, or frame loss statistics derived from transmitted frames which are not ACKed and/or from signaling messages. Finally cross-layer MAC/PHY approaches aim to combine information at both MAC and PHY layers.
Most work on PHY layer approaches is based on SNR and RSSI measurements, for example, D Qiao and S Choi, “Goodput Enhancement of IEEE 802.11a Wireless LAN via Link Adaptation”, Proc. IEEE ICC, 2001; and I. Haratcherev, K. Langendoen, R. Lagendijk and H. Sips, “Hybrid Rate Control for IEEE 802.11”, Proc. ACM, MobiWac, 2004, the disclosures of which are incorporated herein by reference. The basic idea is to a priori map SNR measures into MAC channel quality estimates.
However,                i) SNR/RSSI methods are not able to distinguish between different sources of channel impairment at the MAC layer (e.g. between collision and noise related losses),        ii) the mapping between measured SNR and delivery probability rate is generally specific to each link and may be time varying, see C. Reis, R. Mahajan, M. Rodrig, D. Wetherall, J. Zahorjan “Measurement-Based Models of Delivert and Interference”, Sigcomm 2006, the disclosure of which is incorporated herein by reference, and        iii) the correlation between SNR/RSSI and actual packet delivery rate can be weak, see D Aguayo, et al. “Link-level measurements from an 802.11b mesh network”, Proc. ACM SIGCOMM, 2004, the disclosure of which is incorporated herein by reference.        
With regard to MAC approaches, RTS/CTS signaling can be used to distinguish collisions from channel noise losses, see for example, D J Leith, P Clifford, “A Self-Managed Distributed Channel Selection Algorithm for WLANs”, Proc. IEEE RAWNET, Boston, 2006; and J Kim, et al. “CARA: Collision-Aware Rate Adaptation for IEEE 802.11 WLANs”, Proc. IEEE INFOCOM, 2006, the disclosures of which are incorporated herein by reference. However, such approaches can perform poorly in the presence of hidden nodes and other types of channel impairment.
K J Yu, et al., “A novel hidden station detection mechanism in IEEE 802.11 WLAN”, IEEE Comms Let., 10(8):608-610, August 2006, the disclosure of which is incorporated herein by reference, considers an approximate MAC layer approach for detecting the presence of hidden nodes but does not consider other types of channel impairment.
With regard to combined MAC/PHY approaches, early work related to the present paper is presented in D Malone, et al. “MAC Layer Channel Quality Measurement in 802.11”, IEEE Comms Let., 11(2):143-145, February 2007; and D Giustiniano, et al. “Experimental Assessment of 802.11 MAC Layer Channel Estimators”, IEEE Comms Let., 11(12):961-963, December 2007, the disclosures of which are incorporated herein by reference. However, this uses a channel busy/idle approach that is confined to distinguishing between collision and noise related losses and does not allow consideration of hidden nodes or exposed node and capture effects.